REFAC: Update model loading to use 'tiny.en' for improved performance in Streamlit app

src/streamlit_app.py

@@ -15,7 +15,6 @@ import pandas as pd
 from sklearn.metrics.pairwise import cosine_similarity
 import matplotlib.pyplot as plt
 
-# --- THIS IS THE FINAL FIX ---
 # Create a cross-platform, writable cache directory for all libraries
 CACHE_DIR = os.path.join(tempfile.gettempdir(), "affectlink_cache")
 DEEPFACE_CACHE_PATH = os.path.join(CACHE_DIR, ".deepface", "weights")
@@ -23,7 +22,6 @@ os.makedirs(DEEPFACE_CACHE_PATH, exist_ok=True) # Proactively create the full pa
 
 os.environ['DEEPFACE_HOME'] = CACHE_DIR
 os.environ['HF_HOME'] = CACHE_DIR
-# ===========================
 
 # --- Page Configuration ---
 st.set_page_config(page_title="AffectLink Demo", page_icon="😊", layout="wide")
@@ -48,7 +46,7 @@ AUDIO_SAMPLE_RATE = 16000
 @st.cache_resource
 def load_models():
     with st.spinner("Loading AI models, this may take a moment..."):
-        whisper_model = whisper.load_model("base.en", download_root=os.path.join(CACHE_DIR, "whisper"))
+        whisper_model = whisper.load_model("tiny.en", download_root=os.path.join(CACHE_DIR, "whisper"))
         text_classifier = pipeline("text-classification", model="j-hartmann/emotion-english-distilroberta-base", top_k=None)
         ser_model_name = "superb/hubert-large-superb-er"
         ser_feature_extractor = AutoFeatureExtractor.from_pretrained(ser_model_name)